Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are two types of skin cancer caused by both sunlight and arsenic exposure. It is clear that mutations from UV-induced DNA damage drive sunlight induced skin cancers. In contrast, the mechanism of arsenic induced skin cancer remains unclear. This exploratory project will characterize the differential microRNA expression in primary human keratinocytes exposed long term to arsenic in vitro and in a unique sample set of arsenic induced skin lesions including hyperkeratosis (premalignant lesion to both arsenic induced BCC and SCC), BCC and SCC. MicroRNA expression profiles will be determined by microarray analyses of RNA purified from primary human keratinocytes exposed and unexposed to arsenite in vitro, and in laser capture microdissection purified keratinocytes from formalin fixed paraffin embedded samples of the arsenic induced skin lesions. Differential microRNA expression for the 6 microRNAs with greatest fold change between comparison sets will be confirmed by qRT-PCR. Comparisons between exposed and unexposed primary human keratinocytes will identify arsenic exposure induced changes in microRNA expression that may contribute to cellular transformation. Comparisons between HK vs BCC and HK vs SCC will reveal changes associated with progression from pre-malignant to malignant phenotype, and between BCC vs SCC will reveal similarities and dissimilarities between the two tumor types. Comparison of the microRNA expression profiles unique to arsenic induced BCC and SCC with the published data from sunlight induced BCC and SCC will provide critical molecular information on the similarity or dissimilarity of these phenotypically similar cancers induced by different environmental carcinogens. Completion of these studies will provide novel data on arsenic induced changes in microRNAs in primary human keratinocytes and in progression of arsenic induced skin cancers. Extension of these studies in the future using multiple lesions from single individuals and by combining data with mRNA expression profiles will provide detailed molecular information on tumor progression.